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Journal of Medical Systems

Erschienen in:

01.09.2014 | Education & Training

Brain MR Image Segmentation with Spatial Constrained K-mean Algorithm and Dual-Tree Complex Wavelet Transform

verfasst von: Jingdan Zhang, Wuhan Jiang, Ruichun Wang, Le Wang

Erschienen in: Journal of Medical Systems | Ausgabe 9/2014

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Abstract

In brain MR images, the noise and low-contrast significantly deteriorate the segmentation results. In this paper, we propose an automatic unsupervised segmentation method integrating dual-tree complex wavelet transform (DT-CWT) with K-mean algorithm for brain MR image. Firstly, a multi-dimensional feature vector is constructed based on the intensity, the low-frequency subband of DT-CWT and spatial position information. Then, a spatial constrained K-mean algorithm is presented as the segmentation system. The proposed method is validated by extensive experiments using both simulated and real T1-weighted MR images, and compared with the state-of-the-art algorithms.

http://www.medicalimagecomputing.com/EMS/

http://www.bic.mni.mcgill.ca/brainweb

http://www.cma.mgh.harvard.edu/ibsr

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Titel: Brain MR Image Segmentation with Spatial Constrained K-mean Algorithm and Dual-Tree Complex Wavelet Transform
verfasst von: Jingdan Zhang
Wuhan Jiang
Ruichun Wang
Le Wang
Publikationsdatum: 01.09.2014
Verlag: Springer US
Erschienen in: Journal of Medical Systems / Ausgabe 9/2014
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-014-0093-2

Springer Medizin

Abstract

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